Abstract
We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.
| Original language | English |
|---|---|
| Article number | e0142143 |
| Journal | PLoS ONE |
| Volume | 10 |
| Issue number | 11 |
| DOIs | |
| State | Published - 10 Nov 2015 |
Bibliographical note
Publisher Copyright:© 2015 Bastin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding
We acknowledge support from W. M. Keck Foundation, National Institutes of Health (NIH Grant 1R01- HL098437), the Office of Naval Research (ONR Grant 000141010078), the US-Israel Binational Science Foundation (BSF Grant 2012219), EC- FP7 Marie Curie Fellowship (IIF 628159).
| Funders | Funder number |
|---|---|
| National Institutes of Health | 1R01- HL098437 |
| Office of Naval Research | 000141010078 |
| W. M. Keck Foundation | |
| Seventh Framework Programme | 628159 |
| European Commission | |
| United States-Israel Binational Science Foundation | 2012219 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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